Understanding the response of sorghum cultivars to nitrogen applications in the semi-arid Nigeria using the agricultural production systems simulator

Abstract

The Agricultural Production Systems simulator (APSIM) model was calibrated and evaluated using two improved sorghum varieties conducted in an experiment designed in a randomized complete block, 2014-2016 at two research stations in Nigeria. The results show that the model replicated the observed yield accounting for yield differences and variations in phenological development between the two sorghum cultivars. For earlymaturing cultivar (ICSV-400), the model indicated by low accuracy with root means square error (RMSE) for biomass and grain yields of 20.3% and 23.7%. Meanwhile, Improved-Deko (medium-maturing) cultivar shows the model was calibrated with low RMSE (11.1% for biomass and 13.9% for grain). Also, the model captured yield response to varying Nitrogen (N) fertilizer applications in the three agroecological zones simulated. The N-fertilizer increased simulated grain yield by 26-52% for ICSV-400 and 19-50% for Improved-Deko compared to unfertilized treatment in Sudano-Sahelian zone. The insignificant yield differences between N-fertilizer rates of 60 and 100 kgha À1 suggests 60 kgNha À1 as the optimal rate for Sudano-Sahelian zone. Similarly, grain yield increased by 23-57% for ICSV-400 and 19-59% for Improved Deko compared to unfertilized N-treatment while the optimal mean grain yield was simulated at 80 kgNha À1 in the Sudan savanna zone. In the northern Guinea savanna, mean simulated grain yield increased by 8-20% for ICSV-400 and 12-23% for Improved-Deko when Nfertilizer was applied compared to unfertilized treatment. Optimum grain yield was obtained at 40 kgha À1. Our study suggests a review of blanket recommended fertilizer rates across semi-arid environments for sorghum to maximize productivity and eliminate fertilizer losses, means of adaptation strategies to climate variability.

Delineation of Soil Fertility Management Zones for Site-specific Nutrient Management in the Maize Belt Region of Nigeria

“…Tropical soils (including those in SSA) are characterized by high spatial variability on both macroand/or micro-scales due to the combined effects of intrinsic (e.g., bio-physical and chemical processes) and extrinsic factors (e.g., crop management, fertilizer and tillage, among others) operating at different intensities and on different spatiotemporal scales [9,10]. Spatial variability in soils and the corresponding variability of yield response of various crops to nutrient application have already been observed across SSA [11][12][13][14]. Therefore, uniform fertilizer recommendation and application might result in over application in zones, fields, or soils with high nutrient status and under application in those with low nutrient status.…”

Crop/Plant Modeling Supports Plant Breeding: I. Optimization of Environmental Factors in Accelerating Crop Growth and Development for Speed Breeding

“…2 ). Crop models have been proven to accurately predict the variation in crop growth and development due to changes in environmental factors such as radiation [ 85 ], fertilizer level [ 86 ], irrigation level [ 87 , 88 ], temperature [ 89 ], and CO 2 concentration. For example, in the study of Mohanty et al.…”